Time course transcriptomic analysis of human melanoma A375 cells dying of immunogenic or non immunogenic apoptosis
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE163377 | GEO | 2020/12/17
REPOSITORIES: GEO
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Project description:Detection of immunogenic proteins remains an important task for life sciences as it nourishes the understanding of pathogenicity, illuminates new potential vaccine candidates and broadens the spectrum of biomarkers applicable in diagnostic tools. Traditionally, immunoscreenings of expression libraries via polyclonal sera on nitrocellulose membranes or screenings of whole proteome lysates in 2-D gel electrophoresis are performed. However, these methods feature some rather inconvenient disadvantages. Screening of expression libraries to expose novel antigens from bacteria often lead to an abundance of false positive signals owing to the high cross reactivity of polyclonal antibodies towards the proteins of the expression host. A method is presented that overcomes many disadvantages of the old procedures. We incorporated a fusion tag prior to our genes of interest and attached the expressed fusion proteins covalently on microarrays. This enhances the specific binding of the proteins compared to nitrocellulose. Thus, it helps to reduce the number of false positives significantly. It enables us to screen for immunogenic proteins in a shorter time, with more samples and statistical reliability. We validated our method by employing several known genes from Campylobacter jejuni NCTC 11168. Four of proteins that have previously been described as immunogenic have successfully been assessed immunogenic abilities with our method. One protein with no known immunogenic behaviour before suggested potential immunogenicity. The method presented offers a new approach for screening of bacterial expression libraries to illuminate novel proteins with immunogenic features. It could provide a powerful and attractive alternative to existing methods and help to detect and identify bacterial virulence factors, vaccine candidates and potential biomarkers. The overall study was done with five technical replicates. Ten proteins derived from Campylobacter jejuni were tested regarding their immunogenic potential. The ten proteins derived from Campylobacter jejuni were fusion proteins, i.e., N-terminal HaloTag fused to: Gene <--> Protein cjaA <--> putative amino-acid transporter periplasmic solute-binding protein hisJ <--> histidine-binding protein precursor pal <--> peptidoglycan associated lipoprotein flaC <--> flagellin flaA <--> flagellin peb1a <--> bifunctional adhesin/ABC transporter aspartate/glutamate-binding protein pyrC <--> dihydroorotase (EC:3.5.2.3) pseB <--> UDP-GlcNAc-specific C4,6 dehydratase/C5 epimerase gapA <--> glyceraldehyde 3-phosphate dehydrogenase (EC:1.2.1.12) argC <--> N-acetyl-gamma-glutamyl-phosphate reductase (EC:1.2.1.38)
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2013-12-31 | E-GEOD-38545 | biostudies-arrayexpress
Project description:The response of tumors to PDT treatment is expected to provide information on effects of oxygen depletion, induced apoptosis, induction of an inflammatory response and induction of an ani-tumor immune response. Experiment Overall Design: NCI-H69 human SCLC xenografts were induced in SCID mice. Three pairs of xenograft tumors, PDT treated and untreated controls, were harvested four hours after PDT treatment. RNA was isolated and prepared for hybridization to human Affymetrix GeneChip arrays.
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Project description:We used customized peptide arrays of 163 TXNDC16 peptides to identify immunogenic TXNDC16 epitopes and asked whether discrimination of meningioma and control sera is possible with a specific subset selection of all immunogenic epitopes.
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Project description:Detection of immunogenic proteins remains an important task for life sciences as it nourishes the understanding of pathogenicity, illuminates new potential vaccine candidates and broadens the spectrum of biomarkers applicable in diagnostic tools. Traditionally, immunoscreenings of expression libraries via polyclonal sera on nitrocellulose membranes or screenings of whole proteome lysates in 2-D gel electrophoresis are performed. However, these methods feature some rather inconvenient disadvantages. Screening of expression libraries to expose novel antigens from bacteria often lead to an abundance of false positive signals owing to the high cross reactivity of polyclonal antibodies towards the proteins of the expression host. A method is presented that overcomes many disadvantages of the old procedures. We incorporated a fusion tag prior to our genes of interest and attached the expressed fusion proteins covalently on microarrays. This enhances the specific binding of the proteins compared to nitrocellulose. Thus, it helps to reduce the number of false positives significantly. It enables us to screen for immunogenic proteins in a shorter time, with more samples and statistical reliability. We validated our method by employing several known genes from Campylobacter jejuni NCTC 11168. Four of proteins that have previously been described as immunogenic have successfully been assessed immunogenic abilities with our method. One protein with no known immunogenic behaviour before suggested potential immunogenicity. The method presented offers a new approach for screening of bacterial expression libraries to illuminate novel proteins with immunogenic features. It could provide a powerful and attractive alternative to existing methods and help to detect and identify bacterial virulence factors, vaccine candidates and potential biomarkers.
2011-10-27 | GSE33295 | GEO
Project description:We used customized peptide arrays of 163 TXNDC16 peptides to identify immunogenic TXNDC16 epitopes and asked whether discrimination of meningioma and control sera is possible with a specific subset selection of all immunogenic epitopes. CelluSpotsM-bM-^DM-" peptide arrays were manufactured by Intavis (Germany) with 163 TXNDC16 spanning peptides spotted as two replicate subarrays. 15-mer peptides overlapping by 10 amino acids were covalently bound to cellulose membranes with their C-termini. Please note that the non_normalized.txt contains Ch1 Mean values for all samples (each sequence represented in duplicates) and the identifiers in the 'index' column corresponds to those in the 'index' column in raw gpr files; sample data table contains classification values (for each sequence) described in the sample data processing field.
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